Synopsis
1 Introduction.- 1.1 Motivation.- 1.2 The Need of Interactive Environments.- 1.3 Modern Computer Soft- and Hardware.- 2 Exploratory Statistical Techniques.- 2.1 Descriptive Statistics.- 2.2 Some Stratifications.- 2.3 Boxplots.- 2.4 Quantile-Quantile Plot.- 2.5 Histograms, Regressograms and Charts.- 2.6 Bivariate Plots.- 2.7 Scatterplot Matrices.- 2.8 Three Dimensional Plots.- 2.9 Higher Dimensional Plots.- 2.10 Basic Properties for Graphical Windows.- 3 Some Statistical Applications.- 3.1 Cluster Analysis.- 3.2 Teachware.- 3.3 Regression Methods.- 4 Exploratory Projection Pursuit.- 4.1 Motivation and History.- 4.2 The Basis of Exploratory Projection Pursuit.- 4.3 Application to the Swiss Banknote Dataset.- 4.4 Multivariate Exploratory Projection Pursuit.- 4.5 Discrete Exploratory Projection Pursuit.- 4.6 Requirements for a Tool Doing Exploratory Projection Pursuit.- 5 Data Structures.- 5.1 For Graphical Objects.- 5.2 For Data Objects.- 5.3 For Linking.- 5.4 Existing Computational Environments.- 6 Implementation in XploRe.- 6.1 Data Structures in XploRe 3.2.- 6.2 Selected Commands in XploRe 3.2.- 6.3 Selected Tools in XploRe 3.2.- 6.4 Data Structure in XploRe 4.0.- 6.5 Commands and Macros in XploRe 4.0.- 7 Conclusion.- A The Datasets.- A.1 Boston Housing Data.- A.2 Berlin Housing Data and Berlin Flat Data.- A.3 Swiss Banknote Data.- A.4 Other Data.- B Mean Squared Error of the Friedman-Tukey Index.- C Density Estimation on Hexagonal Bins.- D Programs.- D.1 XploRe Programs.- D.2 Mathematica Program.- E Tables.- References.
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